The Computational Mind Creeps Up on the Digital Humanities

The following white paper discusses a wide range of technologies. I include some excerpts that speak to one of my current hobby horses, that computational is a good metaphor and model for mental processes and thus digital criticism must extend itself in that direction. That doesn't require that one embrace the idea that the mind or brain IS a digital computer, or any other kind of computer, in any simple sense. I certainly don't subscribe to that view. But I do believe something of what the mind does is best characterized as computation and literary studies will benefit by investigating computation as an approximation to literary processes. I've placed the full executive summary at the end.

Meaning and Perspectives in the Digital HumanitiesA White Paper for the establishment of a Center for Humanities and Technology (CHAT)Sally Wyatt (KNAW) and David Millen (IBM) (Eds.)2014 | ISBN 978-90-6984-680-4 | freeKNAW, UvA, VU and IBM are developing a long-term strategic partnership to be operationalized as the Center for Humanities and Technology (CHAT). The members and partners of CHAT will create new analytical methods, practices, data and instruments to enhance significantly the performance and impact of humanities, information science and computer science research.This White Paper outlines the research mission of CHAT. CHAT intends to become a landmark of frontline research in Europa, a magnet for further public-private research partnerships, and a source of economic and societal benefits.
KNAW: Royal Netherlands Academy of Arts and Sciences

Cognitive Computing
The section on cognitive computing begins with a discussion of IBM's Watson technology which, as we all know, defeated the best human contests at Jeopardy!. Watson's "knowledge" was quite superficial, and the paper is upfront about that. But the report does offer this suggestion (pp. 21-22):

The question of how cognitive systems could be applied to the humanities is necessarily a speculative one. Unlike other more established areas, such as text analytics and visualization, cognitive computing is so new that there are no ex- isting humanities applications from which to extrapolate. Nevertheless, there is considerable potential. The capacity to ingest millions of documents and an- swer questions based on their contents certainly suggests useful capabilities for the humanities scholar. The ability to generate multiple hypotheses and gather evidence for and against each one is suggestive of an ability to discover and summarize multiple perspectives on a topic and to classify and cluster documents based on their perspectives,

While we do not expect a cognitive computing system to be writing an essay on the sources of the ideas in the Declaration of Independence any time soon, it might not be unreasonable to imagine a conversation between a scholar and a future descendant of Watson in which the scholar inquires about the origins and history of notions such as ‘self-evident truths’ or ‘unalienable God-given rights’ and carries on a conversation with the system to refine and explore these concepts in the historical literature historical literature and sources. The resulting evidence gathering and the conclusions reached would be a synthesis of human and machine intelligence.

Like many fields, humanities have long been concerned with relationships that can be summarized and analyzed as networks. Most obviously, social net- works connect people with one another. Many humanities scholars also study document networks, such as linked letters. Trade routes may be thought of as another type of network, with both geographic and economic relationships. Linguists create network representations of words and meanings, and study the relationships between language variants across geographies, human mi- grations, ecological changes, and colonialism. Historically significant epidemics also traveled over networks of various kinds – geographical, trade, imperial, and so on.

Contemporary network theory and technologies have transformative potential for the humanities by extending the scale and scope of existing work and by providing a framework for analysis. These approaches have already been brought into some humanities research programs. Literatures of national origins present gods, heroes, and (often) monsters who interact with one ano- ther, and who follow historical or legendary paths and types of relationships. Characters in complex narratives, such as Shakespeare or the conquests of Alexander the Great, engage in network relationships. Analytic approaches to networks permit computation of the relative positions of actors in a network, as well as the strengths of their relationships. Through different types of network metrics, we can discern who is a crucial intermediary, or who is central to a conspiracy.

Has someone been reading Moretti?
Here's what they imagine for the future:

In the future, we envision a suite of network analytic instruments, suitable for humanities data and questions. These instruments will be broadly available and They will support derivation of network structures from the kinds of mark-ups that are already a part of digital humanities practices, such as enhanced versions of TEI, OAC, and YAML (see section about Text and Social Analytics). The existing network analytics, which have already proven useful in representing history and commerce, will be extended to support specific in the humanities needs emerging from more formal analyses of narratives and poetry. Concept networks will become more important in the analysis of gen- res, argumentation, and close readings of literary works. The humanities can increase the scope and scale of their work and their impact, and can inform network thinking by bringing specifically humanities-based concepts into the broader discussions of network analysis and representation.

Relations in networks are more and more interpreted and typed, eventually leading to formally structured graphs in representations such as RDF, VNA, or DL. These representations lead to an Open Linked Humanities infrastructure, in analogy to the Linked Open Data project (LOD), in which data are semantically anchored and linked. Such an Open Linked Humanities framework allows for new ways of network analysis (e.g. exploiting semantic generalization) and visualizations, such as graph exploration, timelines, and interactive maps.

At this point, all of this is pie in the sky. Some of it will work out, some won't, and things we've not yet imagined will turn up. That's what happens when you explore new territory. No one knows what's out there, but we have every reason to believe there are intellectual adventures waiting for us.
Executive Summary
(pp. 8-10)
The Royal Netherlands Academy of Arts and Sciences (KNAW), University of Am- sterdam (UvA), VU University Amsterdam (VU), Netherlands eScience Center (NLeSC) and IBM are developing a long-term strategic partnership to be opera- tionalized as the Center for Humanities and Technology (CHAT). The members and partners of CHAT will create new analytical methods, practices, data and instruments to enhance significantly the performance and impact of humanities, information science and computer science research. The anticipated benefits of this partnership include: 1) transformational progress in humanities research and understanding to address societal challenges, 2) significant improvements in algorithms and computational instruments that deal with heterogeneous, complex, and social data, and 3) societal benefits through novel understandings of language, culture, and history.
Four important humanities challenges have been identified, relating to the ways in which perspectives, context, structure and narration can be understood. More specifically, these can be expressed as: understanding changes in meaning and perspective, representing uncertainty in data sources and knowledge claims, understanding how patterns and categories are made and stabilized, capturing latent and implicit meaning, and moving from sentiment mining to emotional complexity.
We see many important scientific and technical challenges that promise breakthrough scholarship in the humanities. The work in CHAT will focus on the following areas: Cognitive Computing, Network Analytics, Visualization, Text and Social Analytics, and Search and Data Representation.

Cognitive Computing: Cognitive computing systems collaborate with hu- mans on human terms, using conversational natural language as well as visual and touch interfaces. We envision cognitive systems will be able to learn and reason, to interact naturally with humans, and to discover and decide using deep domain knowledge.

Network Analytics: Contemporary network theory and technologies have transformative potential for the humanities by extending the scale and scope of existing work and by providing a framework for analysis.

￼￼Visualization: Access to large, multimodal datasets has created both chal- lenges and opportunities for humanities researchers. New visualization instruments are required for interactive discovery of meaning across time and integrating multiple modalities. Progress is also needed in the underlying analytics on which these multi-layered visualizations are produced.

￼Text and Social Analytics: With current text analytics, we can perform computation of attributes of text, pattern detection, theme identification, information extraction, and association analysis. We envision ongoing im- provements in lexical analysis of text, topic extraction and summarization, and natural language processing (NLP) of meaning and associations within the text.

￼Search and Data Representation: One of the key challenges in modern information retrieval is the shift from document retrieval to more meaningful units such as answers, entities, events, discussions, and perspectives. Advances in this area will help humanities scholars in important exploration and contextualization tasks.

￼In addition to the underlying core technologies described above, significant challenges are also present in both the computing and collaboration infrastructures to achieve the desired transformation of digital humanities scholarship. Hosted services for ‘big data’ must deliver easy access to both historical and ‘born digital’ data that comprise contemporary digital humanities research. Innovative collaborative platforms, social learning approaches, and new work practices are needed to promote and support data sharing and collaboration across multi-disciplinary, distributed research teams.
Transforming both humanities and computer science research will equip CHAT to contribute to meeting important societal challenges. Computers and computational methods, since their widespread development and diffusion in the second half of the 20th century, have transformed the ways in which people work, communicate, play, and even think. Humanities research contributes substantially to the development of the human spirit, and to critical reflection, especially in debates about social inclusion, multiculturalism, and the role of creativity in education, work, and elsewhere. Humanities research also makes a vital contribution to many sectors of economic and cultural life, including media, heritage, education, and tourism. Humanities research has also contributed to innovations in computer technology, for example via predictive text, now available on all mobile devices. We believe that collaboration among humanities and computer science researchers in CHAT will lead to significant breakthroughs in both areas, and will benefit many other areas of social, technical and cultural activity.